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Deep reinforcement learning for robotics: A survey of real-world successes
Reinforcement learning (RL), particularly its combination with deep neural networks,
referred to as deep RL (DRL), has shown tremendous promise across a wide range of …
referred to as deep RL (DRL), has shown tremendous promise across a wide range of …
Deep reinforcement learning based mobile robot navigation: A review
K Zhu, T Zhang - Tsinghua Science and Technology, 2021 - ieeexplore.ieee.org
Navigation is a fundamental problem of mobile robots, for which Deep Reinforcement
Learning (DRL) has received significant attention because of its strong representation and …
Learning (DRL) has received significant attention because of its strong representation and …
Badgr: An autonomous self-supervised learning-based navigation system
Mobile robot navigation is typically regarded as a geometric problem, in which the robot's
objective is to perceive the geometry of the environment in order to plan collision-free paths …
objective is to perceive the geometry of the environment in order to plan collision-free paths …
Adaptive power system emergency control using deep reinforcement learning
Power system emergency control is generally regarded as the last safety net for grid security
and resiliency. Existing emergency control schemes are usually designed offline based on …
and resiliency. Existing emergency control schemes are usually designed offline based on …
Search on the replay buffer: Bridging planning and reinforcement learning
The history of learning for control has been an exciting back and forth between two broad
classes of algorithms: planning and reinforcement learning. Planning algorithms effectively …
classes of algorithms: planning and reinforcement learning. Planning algorithms effectively …